bioRxiv Science⌕ Search

bioRxiv · 10.1101/838433

Proposed mechanism of kinesin backstepping

Abstract

Kinesin-1 is an ATP-driven molecular motor that transports cellular cargo along microtubules. At low loads, kinesin-1 almost always steps forwards, towards microtubule plus ends, but at higher loads, it can also step backwards. Backsteps are usually 8 nm, but can be larger. These larger backwards events of 16 nm, 24 nm or more are thought to be slips rather than steps, because they are too fast to consist of multiple, tightly-coupled 8 nm steps. Here we propose that not just these larger backsteps, but all kinesin-1 backsteps, are slips. We show firstly that kinesin waits before forward steps for less time than before backsteps and detachments; secondly that kinesin waits for the same amount of time before backsteps and detachments and thirdly that by varying the microtubule type we can change the ratio of backsteps to detachments, without affecting forward stepping. Our findings indicate that backsteps and detachments originate from the same state and that this state arises later in the mechanochemical cycle than the state that gives rise to forward steps. To explain our data, we propose that in each cycle of ATP turnover, forward kinesin steps can only occur before Pi release, whilst backslips and detachments can only occur after Pi release. In the scheme we propose, Pi release gates access to a weak binding K.ADP-K.ADP state that can slip back along the microtubule, re-engage, release ADP and try again to take an ATP-driven forward step. We predict that this rescued detachment pathway is key to maintaining kinesin processivity under load. Significance statementKinesin-1 molecular motors are ATP-driven walking machines that typically step forward, towards microtubule plus ends. But they can also step backwards, especially at high load. Backsteps are currently thought to occur by directional reversal of forwards walking. To the contrary, we propose here that kinesin backsteps are not steps, but slips. We show that backwards translocations originate from a different and later state in the kinesin mechanism than the state that generates forward steps. To explain this, we propose that following ATP binding, kinesin molecules that fail to step forward within a load-dependent time window convert to a state that can slip back, rebind to the microtubule, and try again to step forward.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Toleikis, A., Carter, N. J., Cross, R. A.. 2019-11-12. Proposed mechanism of kinesin backstepping. https://doi.org/10.1101/838433

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Design of colipids with controlled lateral distance of head group moieties for targeting strategies in the field of lipid-based nanoparticles

Lipid nanoparticles and liposomes are nanoparticle drug formulations which are firmly established in clinics. In order to expand their application and improve efficacy, surface modifications can be a key strategy, especially for cell specific targeting. Targeting can be achieved by integrating ligand functionalized lipids or lipidoids on the nanoparticle surface. In this case, not solely the targeting ligand itself, but also the structure of the whole targeting lipid/lipidoid can affect the interaction of the targeting ligand with the binding motive on cells. Especially, distal spacer structures between lipid anchor and ligand unit, often composed of polyethylene glycol chains, provide a certain distance of the ligand from the nanoparticle surface. A concept which is currently neglected is the control of the lateral distance between ligand structures on the nanoparticle. Herein we investigated the possibility to design lipidoids with a lateral spacer composed of polyethylene glycol units. We synthesized and characterized different lipidoids which provide a primary amine in the head group for possible ligand coupling. In our model lipidoids the head groups were functionalized with a paramagnetic probe to apply electron paramagnetic resonance (EPR) methods for the characterization of the lipidoid interaction with model nanoparticles, in our case liposomes. Continuous wave EPR was used to study the efficiency of the novel lipidoids to integrate into lipid bilayers of model liposomes, which was shown to depend on lipidoid structure and liposome composition. Furthermore, using double electron-electron resonance (DEER), we observed lipidoid conformational changes occurring upon integration into liposomes.

biophysics↗

Beyond Sequence and Structure: Pretraining PLMs on Continuous Biophysical Fields

We introduce the Biophysical Transformer, a protein language model that adds continuous biophysical fields as a third pretraining signal beside sequence and structure. A Poisson-Boltzmann solver computes the electrostatic potential around each three-residue token, and the model learns to predict it from sequence alone. A rotationally invariant spherical-harmonic descriptor serves as the loss target, eliminating the need for frame alignment during training and for coordinates at inference. Against a matched, one-flag control on the FLIP Meltome thermostability benchmark, the field objective raises Spearman correlation on every trained head of both human splits.The gain on human survives residualizing dipeptide composition under two architecturally different readouts and survives removing the test proteins that overlap the pretraining corpus. No effect survives on the organism-mixed split. At 1.1M parameters, both the Biophysical Transformer and its sequence-only control exceed FLIP's one-hot CNN and untrained-ESM baselines on every split. All results rest on a single pretraining run per arm,and the current design does not separate field content from generic regularization.

biophysics↗

An auditable harness for biomolecular dynamics simulations by AI agents

AI agents now generate biological hypotheses faster than they can be tested. Hypotheses stated at the atomic level can be examined with molecular dynamics (MD) simulations. For new questions without a reference, trust in an agent-run simulation rests on a tool-written process record, not the agent's account. Existing MD agents leave this record to the language model. Here we present MDClaw, a harness whose validating tools and directed acyclic graph (DAG) check stages before execution and record every simulation stage. On MDDataBench, which grades outputs against deposited simulations, four open-weight models with MDClaw passed all three runs on 81-100% of 31 test systems. The DAG complements this outcome check. An ablation without the DAG revealed 11 successful runs that had skipped minimization or equilibration, or simulated a different structure. MDClaw carried questions from human and AI scientists through simulation to trajectories traceable to their inputs and settings.

biophysics↗